Coronary artery disease and other heart-related diseases are very prevalent, especially in western civilizations, and lead to the death of many people each year. By detecting heart related diseases as early as possible, appropriate, effective and cost-effective treatment can be implemented to reduce fatality. In the field of cardiology, various systems and techniques are used for accurate and early detection of heart disease.
For instance, angiography is one method that can be used for directly measuring coronary occlusion (i.e., blockage of the coronary arteries due to calcification). However, these measurements often require invasive procedures. Furthermore, although angiography can be used to identify and measure occlusions, such methods cannot measure or otherwise assess the effects of such occlusions. Indeed, the effect of coronary occlusion is typically manifested regionally within the heart wall, resulting in abnormalities of myocardial tissue or myocardial function. For instance, infarction is a condition that refers to the development of an area of dead or dying myocardial tissue (infarct) due to inadequate blood flow through the coronary vessels that normally supply blood to the myocardial tissue.
Typically, methods for assessing myocardial function are performed by analyzing wall motion through cardiac imaging to identify wall motion abnormalities. In general, in the field of medical imaging, various imaging modalities and systems can be used for generating medical images of anatomical structures of individuals for screening and evaluating medical conditions. These imaging systems include, for example, CT (computed tomography) imaging, MRI (magnetic resonance imaging), NM (nuclear magnetic) resonance imaging, X-ray systems, US (ultrasound) systems, PET (positron emission tomography) systems, etc. Each imaging modality may provide unique advantages over other modalities for screening and evaluating certain types of diseases, medical conditions or anatomical abnormalities, including, for example, cardiomyopathy, colonic polyps, aneurisms, lung nodules, calcification on heart or artery tissue, cancer micro calcifications or masses in breast tissue, and various other lesions or abnormalities.
Due to its availability, relative low cost, and noninvasiveness, cardiac ultrasound is an imaging modality that is typically used for performing wall motion analysis for purposes of assessing cardiac functions (e.g., assessing regional systolic wall motion abnormalities). By way of example, analyzing ventricle motion is an efficient way to evaluate a degree of ischemia and infarction. In particular, wall motion analysis of the endocardium wall over one heartbeat, or a prescribed portion of the heartbeat, can be performed to quantify the elasticity and contractility of the left ventricle or to otherwise detect and diagnose wall motion abnormalities.
Conventional methods for assessing myocardial function include manual and automated methods for analyzing wall motion using cardiac imaging such as ultrasound (echocardiography). For instance, manual methods for quantifying left ventricular function include manually tracing endocardial and epicardial borders (counters) that are identified within still ultrasound frames at different portions of the cardiac cycle and obtaining various measurements related to wall motion from the traced borders. With some conventional methods, equations are then applied to the results of such measurements, which make certain geometric assumptions and may include empirically derived modifications to a mathematical model. The results are typically viewed in tabular format on a report page and interpretation of such results requires knowledge of normal ranges.
Another conventional manual method for wall motion analysis in echocardiography (e.g., stress echo) includes segmental wall motion analysis, which requires significant training and experience on the part of the echo cardiographer. With such method, the walls of the left ventricle are divided into a plurality of segments (e.g., 16 or 17) according to a prevailing model recommended by the American Society of Echocardiography (ASE). Various standard ultrasound views are obtained to acquire image data information for each LV segment, wherein the standard views are obtained such that the plurality of segments roughly align with a presumed distribution of the three major coronary artery segments. The echo cardiographer will then visually inspect the acquired image data to assess global function and regional abnormalities and then based on his/her assessment, assign a wall motion score to each segment in accordance with a an ASE recommended standard scoring scheme. In particular, the echo cardiographer will visually assess the absolute and relative segmental systolic excursion and timing of excursion to provide some qualitative assessment of each imageable segment. The collective assessments result in a report of negative (non-pathological) or positive (pathological) findings.
A primary concern in the field of echocardiography is the variability in wall motion scoring due to the subjectivity in analyzing wall motion, especially for stress echocardiography, which presents a significant impediment to, e.g., diagnosis of coronary artery disease. Indeed, the accuracy of such echocardiogram reports are directly related to the experience of the operator. Indeed, there is often more “art” involved in such diagnosis than “science.” Cardiologists stress the importance of improving wall motion scoring in echocardiography.
Conventional methods for assessing myocardial function include automated methods for analyzing wall motion using cardiac imaging. For example, one conventional method includes automated border detection based on analysis of integrated backscatter, which provides an automated estimate of LV function indices, but does not address segmental or global wall function. Other methods for automatic wall motion analysis generate parametric images indicating excursion, but provide no quantitative comparison amongst segments. One conventional method known as the automated segmental motion analysis (A-SMA) system includes methods for automated border detection to determine the LC cavity and surrounding tissue, and displaying a parametric image of fractional area change. This index was also displayed as a numeric graph for six segments equi-spaced segments in the parasternal short axis view.
While automated methods for wall motion analysis can provide parametric images and generate indices related to wall motion, such methods do not provide automated assessment, or otherwise identify or characterize the condition (e.g., normal or abnormal) of the myocardial tissue.